docs: def _F(x, gam):
          """
          Eqs. A6, A7 of Baring et al. (1999)
          """
          beta = np.sqrt(1 - gam ** -2)
          B = 1 + 0.5 * (gam ** 2 - 1)
          C = 10 * x * gam * beta * (2 + gam * beta)
          C /= 1 + x ** 2 * (gam ** 2 - 1)
  
          F_1 = (17 - 3 * x ** 2 / (2 - x) ** 2 - C) * np.sqrt(1 - x)
          F_2 = 12 * (2 - x) - 7 * x ** 2 / (2 - x) - 3 * x ** 4 / (2 - x) ** 3
          F_3 = np.log((1 + np.sqrt(1 - x)) / np.sqrt(x))
  
          return B * F_1 + F_2 * F_3